Various receiver types use so-called “combining weights” for received signal processing, including data symbol demodulation and/or signal quality estimation. For example, linear receivers find widespread use in wireless communication networks, e.g., as implemented by wireless devices or other apparatuses that are configured for operation in such networks.
A linear receiver that implements minimum-mean-square-error, MMSE, processing operates as a combiner, according to a set or vector of combining weights W. The combining weights W are determined so as to minimize the error between symbol values as detected from the received signal r and the corresponding actual transmitted symbol values. See WO 2013/050985 A2, as published on 11 Apr. 2013, for example details regarding MMSE operation.
As is well understood by those of ordinary skill in the art, these combining weights may be calculated as W=R−1H, where H denotes a vector or set of the relevant propagation channel estimates and where R denotes a covariance matrix characterizing the noise and/or interference in the desired signal. The covariance is determined as between received signal streams corresponding to different path delays and/or different receiver antennas.
The matrix R is referred to herein as the “overall covariance matrix” and it may be defined as R=E{rrH}, where “E” denotes expected value. In general, any “covariance matrix” referred to in this disclosure shall be understood as characterizing noise and/or interference, unless otherwise noted.
An apparatus operating in a cellular communication network generally receives an own-cell signal from a serving cell and one or more other-cell signals from other cells, e.g., from neighboring cells that are within radio range of the apparatus. Correspondingly, the overall covariance matrix R represents a combination of covariance characterizing noise and/or interference associated with own-cell transmissions and with other-cell transmissions. The own-cell covariance term in R characterizes noise and/or interference arising from multi-stream MIMO transmissions in the serving cell. The other-cell covariance term in R characterizes noise and/or interference from one or more other-cell transmissions that are received by the apparatus as interfering transmissions. The other-cell covariance term may be denoted by the covariance matrix Rother.
In a Long Term Evolution, LTE, example, an apparatus operating in an LTE network receives a composite signal that includes an own-cell signal from its serving cell and other-cell signals transmitted in other cells that are nearby. According to the LTE specifications, these signals are synchronized and include defined control and data regions. The own-cell signal includes Cell-specific Reference Symbols or CRS that are specific to that cell but not specific to any particular apparatus operating in the cell. The CRS are distributed across the control and data regions of the own-cell signal and they serve as common pilot symbols for all apparatuses operating in the cell. A data transmission within the data region of the own-cell signal also may include Demodulation Reference Symbols or DMRS, which are precoded for the apparatus targeted by that data transmission. The DMRS thus serve as a type of dedicated pilot that provides for enhanced channel estimation with respect to the data transmission.
These common and dedicated pilot symbols are used by the apparatus to estimate the own-cell channel H. By convention, they are further used to estimate the overall and other-cell covariance matrices R and Rother. Other-cell covariance may be particularly significant in certain transmission environments, such as in a heterogeneous network that comprises a mix of macro and pico cells. As suggested by the terminology, the pico cells provide service over limited geographic areas or zones in comparison to the macro cells. Correspondingly, the pico cells are provided by base stations or other radio nodes that are typically much lower in power than the radio node(s) providing the macro cells. Consequently, an apparatus operating near the edge of a pico cell edge may suffer significant levels of other-cell interference from one or more neighboring macro cells.
Accurate estimation of the other-cell covariance Rother is critical for accurate estimation of the overall covariance matrix R, which in turn is critical for accurate determination of the combining weights W. It is recognized herein that the relatively small number of pilot symbols available in the own-cell signal for estimation of Rother reduces the quality of covariance estimation. That reduction in quality causes receiver performance to suffer, which in turn reduces data throughput to such receivers and thus lowers overall network throughput and efficiency.